WrenAI docker-compose file error

ERROR An error occurred: 1 error(s) decoding:

      * 'services[wren-ai-service].ports[0]' expected a map, got 'string

Feb 11 '25 04:02 JunChenMoCode

@202252197 hi, have u tried launching Wren AI using release artifact?

Please check the official installation method here: https://docs.getwren.ai/oss/installation#using-wren-ai-launcher

Feb 11 '25 04:02 cyyeh

I used the link provided above to install wren ai and got the same bug! it occurs when you try to use your own local model instead of default gpt api.

Feb 21 '25 16:02 Ahmed-ao

I guess that you didn't create the .env file with all the parameters. Use this file as example: https://github.com/Canner/WrenAI/blob/main/docker/.env.example

Feb 25 '25 21:02 joanteixi

I used your .env file and it worked. However the is a problem with yaml config file; it doesn't connect to local model. I'm trying to use Deepseek:14b locally with Ollama. and I followed the instruction provided here https://docs.getwren.ai/oss/installation/custom_llm

Yaml Config

`type: llm provider: litellm_llm timeout: 600 models:

model: openai/deepseek-r1:14b api_base: http://docker.host.internal:11434/v1 api_key_name: LLM_OLLAMA_API_KEY kwargs: temperature: 0.8 n: 1
for better consistency of llm response
seed: 0 max_tokens: 4096 response_format: type: text
model: openai/deepseek-r1:14b api_base: http://docker.host.internal:11434/v1 api_key_name: LLM_OLLAMA_API_KEY kwargs: temperature: 0.8 n: 1
for better consistency of llm response
seed: 0 max_tokens: 4096 response_format: type: text

type: embedder provider: litellm_embedder models:

model: openai/nomic-embed-text dimension: 768 url: http://host.docker.internal:11434/v1 timeout: 120

type: engine provider: wren_ui endpoint: http://localhost:3000

type: engine provider: wren_ibis endpoint: http://localhost:8000 source: bigquery manifest: '' # base64 encoded string of the MDL connection_info: '' # base64 encoded string of the connection info

type: engine provider: wren_engine endpoint: http://localhost:8080 manifest: ''

type: document_store provider: qdrant location: http://qdrant:6333 embedding_model_dim: 768 timeout: 120 recreate_index: true

type: pipeline pipes:

name: deepseek_pipline llm: litellm_llm.openai/deepseek-r1:14b embedder: litellm_embedder.openai/nomic-embed-text
other pipeline configurations
name: db_schema_indexing embedder: litellm_embedder.openai/nomic-embed-text document_store: qdrant
name: historical_question_indexing embedder: litellm_embedder.openai/nomic-embed-text document_store: qdrant
name: table_description_indexing embedder: litellm_embedder.openai/nomic-embed-text document_store: qdrant
name: db_schema_retrieval llm: litellm_llm.openai/deepseek-r1:14b embedder: litellm_embedder.openai/nomic-embed-text document_store: qdrant
name: historical_question_retrieval embedder: litellm_embedder.openai/nomic-embed-text document_store: qdrant
name: sql_generation llm: litellm_llm.openai/deepseek-r1:14b engine: wren_ui
name: sql_correction llm: litellm_llm.openai/deepseek-r1:14b engine: wren_ui
name: followup_sql_generation llm: litellm_llm.openai/deepseek-r1:14b engine: wren_ui
name: sql_summary llm: litellm_llm.openai/deepseek-r1:14b
name: sql_answer llm: litellm_llm.openai/deepseek-r1:14b engine: wren_ui
name: sql_breakdown llm: litellm_llm.openai/deepseek-r1:14b engine: wren_ui
name: sql_expansion llm: litellm_llm.openai/deepseek-r1:14b engine: wren_ui
name: sql_explanation llm: litellm_llm.openai/deepseek-r1:14b
name: sql_regeneration llm: litellm_llm.openai/deepseek-r1:14b engine: wren_ui
name: semantics_description llm: litellm_llm.openai/deepseek-r1:14b
name: relationship_recommendation llm: litellm_llm.openai/deepseek-r1:14b engine: wren_ui
name: question_recommendation llm: litellm_llm.openai/deepseek-r1:14b
name: question_recommendation_db_schema_retrieval llm: litellm_llm.openai/deepseek-r1:14b embedder: litellm_embedder.openai/nomic-embed-text document_store: qdrant
name: question_recommendation_sql_generation llm: litellm_llm.openai/deepseek-r1:14b engine: wren_ui
name: chart_generation llm: litellm_llm.openai/deepseek-r1:14b
name: chart_adjustment llm: litellm_llm.openai/deepseek-r1:14b
name: intent_classification llm: litellm_llm.openai/deepseek-r1:14b embedder: litellm_embedder.openai/nomic-embed-text document_store: qdrant
name: data_assistance llm: litellm_llm.openai/deepseek-r1:14b
name: sql_pairs_indexing document_store: qdrant embedder: litellm_embedder.openai/nomic-embed-text
name: sql_pairs_deletion document_store: qdrant embedder: litellm_embedder.openai/nomic-embed-text
name: sql_pairs_retrieval document_store: qdrant embedder: litellm_embedder.openai/nomic-embed-text llm: litellm_llm.openai/deepseek-r1:14b
name: preprocess_sql_data llm: litellm_llm.openai/deepseek-r1:14b
name: sql_executor engine: wren_ui
name: sql_question_generation llm: litellm_llm.openai/deepseek-r1:14b
name: sql_generation_reasoning llm: litellm_llm.openai/deepseek-r1:14b

settings: host: 127.0.0.1 port: 5556 column_indexing_batch_size: 50 table_retrieval_size: 10 table_column_retrieval_size: 100 query_cache_maxsize: 1000 allow_using_db_schemas_without_pruning: false query_cache_ttl: 3600 langfuse_host: https://cloud.langfuse.com langfuse_enable: true logging_level: INFO development: false `

Feb 26 '25 21:02 Ahmed-ao

Hi @Ahmed-ao, here is my config.yaml for Ollama model and embedder. I think you can base it on it and modify it to your version.

models:
- api_base: http://host.docker.internal:11434/
  kwargs:
    n: 1
    temperature: 0
  model: ollama/phi4
provider: litellm_llm
timeout: 120
type: llm
---
models:
- api_base: http://host.docker.internal:11434/
  model: ollama/nomic-embed-text
  timeout: 120
provider: litellm_embedder
type: embedder

Mar 03 '25 10:03 paopa

docker-compose file error

Yaml Config

for better consistency of llm response

for better consistency of llm response

other pipeline configurations